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AI needs science’s search history
“Actually, that’s where the gold is,” said Alasdair Russell, my graduate school friend who leads a pre-clinical genome editing group at Cambridge. He was talking about the winding road of science that is omitted from published papers. “When you’re discussing how to do the experiment, and why this way is better than another way, and what does the data really mean? I know what it shows, but what does it mean?” At RAAIS 2026, he described how his group has begun logging the twisting path of discovery as it happens, recording the verbal and written exchanges that normally disappear. Ideas become nodes in a living graph: they branch when a meeting produces two plausible experiments, merge when separate lines of evidence converge, and go dark when someone quietly stops pursuing them. In his implementation, one agent scores novelty, while another tries to learn “how scientists think and how they navigate through a complex world of data,” so that high-potential nodes can trigger deeper investigation. As frontier AI labs deploy agents toward scientific discovery, giving AI authentic scientific taste remains a trillion-dollar dilemma. The bottleneck is that the record we have kept for centuries of science might be insufficient to get us there. The experiments that never make the paper Peter Medawar, 1960 Nobel laureate and “father of transplantation,” asked in 1963 whether the scientific paper was a fraud, and answered yes: the form of the paper misrepresents the thinking that produced it. Sixty years on, the diagnosis is unchanged. A paper presents a clean progression from hypothesis to result to conclusion. Lost along the way are the unconventional theories, the abandoned or unaffordable methods, and the underwhelming and inconclusive data. It reads like a browser history with every dead end deleted: the ten open tabs, the four rephrased queries, the wrong turn down a subforum. All scrubbed, leaving one clean path from question to answer as the canonical path. What has changed since then is that the discarded material is now worth something. No high-impact journal wants these artifacts, but raw trial and error is the most likely source of the training data required to develop scientific intuition, or what researchers call taste. Earlier attempts to capture the discards were motivated by scientific integrity. The Journal of Negative Results in Biomedicine launched in 2002 to publish rigorous studies that disputed established models or exposed ineffective treatments. Its archive preserved negative conclusions after they had become papers, rather than the live alternatives and arguments that produced them. BioMed Central closed it in 2017, saying the mission had been served now that other journals publish null results. A less generous reading is that in fifteen years it published around 200 papers because almost nobody wants to read a negative result, let alone write one up when it will not count toward academic tenure. AI models are different. Even an uninteresting negative result can be useful, provided it is labeled. Earlier this year, Anthropic put a version of this to the test. The company pulled 129 decision points from real Claude Code sessions between January and March 2026, showed models the work up to a human detour, and asked what should happen next. Claude Mythos Preview beat the human choice 64% of the time, while Opus 4.5 managed 51%. The comparison was tilted toward the models because Anthropic deliberately chose moments where the human decision had room for improvement. On 127 further scenarios where the human action was already strong, the models improved on it only about 20% of the time. The study was possible because Anthropic’s researchers work inside a tool that logs by default. The reasoning, detours and outcome are produced in the same working environment. Biology has no equivalent. Its reasoning happens in hallways, at benches, in Slack threads and on whiteboards, while the outcome arrives weeks later somewhere else. The record has to emerge from the work itself. Ask scientists to reconstruct it afterwards and we’ll create another polished account. Subscribe A log is not a label Before any of this becomes training data, a negative result has to say what failed. The first paper published in the Journal of Negative Results in Biomedicine examined 234 negative studies across five leading medical journals. Only 30% discussed statistical power, and half clearly defined a primary outcome. Tell a model an experiment failed, without telling it whether the assay was underpowered, a reagent had degraded, or the hypothesis was simply wrong, and it will learn noise with confidence. Decision histories have a second missing label too. When a lab considers five experiments and runs one, only the chosen branch returns an outcome. The other four are experimental counterfactuals. Researchers call this the selective labels problem: the data reveal results only for the actions someone chose to take. Such a record can teach a model to imitate a lab’s taste, but it cannot establish that the taste was good. It also smuggles local constraints into general lessons. A lab that never ran cryo-EM because it did not own a microscope teaches a model that cryo-EM is rarely the right call. Alasdair’s nodes preserve the candidate set, which is the necessary first step. To be useful, each decision record needs six fields: The evidence available at that moment, and nothing that arrived later. The candidates considered, including the ones dismissed in a sentence. For each candidate: the expected result, the confidence attached to it, and the cost in time and money. The route chosen, and the reason. What happened next. How the evidence changed the scientist’s view. These must be timestamped before the outcome, because hindsight turns uncertainty into inevitability. Disagreement also has to survive. Averaging three scientists into one clean rationale reproduces exactly the information loss we are trying to fix. But there is an obvious failure mode here. Once decisions are logged and scored, people log for the record post-facto. Anyone who has watched an electronic lab notebook fill up with retrospective tidying knows how quickly a research tool becomes a compliance exercise. A record that costs a scientist ten minutes of honest reflection per decision is worth far more than one that costs an hour of performance. A publication initiative called Registered Reports offers a useful starting point. Here, researchers submit their rationale, methods and analysis plan for peer review before the data exist, and the journal commits in principle to publish if they follow the approved plan. Nature has now expanded the format across every field it covers. This approach to paper writing timestamps intent before the outcome, but it freezes one plan. A useful search history must also preserve how the plan changed, which alternatives were rejected, when, and on what evidence. Subscribe Run the runner-up Autonomous labs show what happens when decisions and outcomes are connected in a loop. Liverpool’s mobile robotic chemist ran 688 experiments over eight days in a ten-variable formulation space. A batched Bayesian search used each result to choose the next experiments and found photocatalyst mixtures six times more active than the starting formulations. Every completed experiment changed what the system did next. The robot optimized within a goal and search space that humans had already chosen. It did not decide which scientific question mattered. So what this work demonstrates is narrower, but still useful: a search history pays off when the options return standardized outcomes quickly. Open-ended biology is harder because branches can take weeks and the discarded alternatives may never be run. Some exploration therefore has to be bought. Where two branches are plausible and the stakes justify the cost, a lab should sometimes run the runner-up. Otherwise the record captures what today’s scientists usually chose and stays silent on what they systematically overlooked. A funder could ring-fence a small fraction of a grant for the branch not taken, provided that the decision record and the outcome are both deposited. That costs money, but so does having every lab rediscover the same abandoned path. Test whether taste transfers When it comes time to evaluate if our new AI system exhibits taste, the comparison should run across laboratories and fields. At selected decision points in a live research campaign, we should freeze the six fields: the evidence, the candidates, expected results, confidence, costs and the choice made. Experts then rank the options before the outcomes are known, and those outcomes are checked independently later. We could give models one of two diets - papers alone, or papers plus decision histories - and ask them to rank the next experiment on unfamiliar projects. Then, we score information gained per dollar and week, calibration, and how quickly weak branches are abandoned. If histories improve choices only inside the lab that produced them, they amount to useful organizational memory. If they improve choices on unfamiliar problems elsewhere, Alasdair’s group will have captured something science has never managed to write down: a transferable record of taste. Until that happens, a scientific search history is a promising record, not yet a training set.
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Cerebras Systems Fast Inference Cloud Business Nearly Quadruples in Second Quarter 2026
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Energy Department wants to create science-specific AI models
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Digital Science brings real-world research impact data into AI workflows with new Altmetric MCP
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Viewpoint: Europe needs a new scientific contract
The White House's new science strategy should be required reading in the Berlaymont and every European capital.Not because Europe should copy it. Parts of it should concern Europeans deeply. But because it asks the question Europe has so far avoided while steadily losing ground in the global race for technological leadership.Europe already possesses many of the world's finest universities, scientists and research-intensive companies. It produces world-leading research in fields ranging from quantum technologies and biotechnology to climate science. Yet time and again Europe generates the scientific breakthroughs while others build the companies, industries and strategic advantages around them, particularly in digital technologies. Increasingly, we find ourselves regulating technologies whose underlying capabilities were developed elsewhere.This is not primarily a scientific failure. It is an institutional one.The settlement that shaped modern science policy emerged after the Second World War. In Science, the Endless Frontier, Vannevar Bush argued that governments should invest in fundamental research while protecting scientists from political direction. Public investment was justified precisely because no government, university or company could predict where the next transformative discovery would emerge.That scientific contract served liberal democracies extraordinarily well. It underpinned decades of advances in medicine, computing, energy and communications, but the world for which it was designed no longer exists.Artificial intelligence is transforming not only technology but the production of knowledge itself. Advanced chips, computing power, data and scientific instruments have become strategic assets. Scientific knowledge now diffuses globally almost instantly. Competitive advantage increasingly lies not in making discoveries first, but in possessing the infrastructure, capital, engineering capability and institutions required to translate those ideas into products, industries and strategic advantage.The old boundaries between science, industrial policy, national security and geopolitics have largely disappeared. Dual-use technologies now underpin both economic power and military deterrence.The US has recognised this shift. In July, the White House published Science: A New Golden Age, a comprehensive attempt to rethink the relationship between science and national power. The report builds on Bush's legacy, but departs from his framework in important ways. Science is no longer treated simply as the source of future discoveries. It is presented as the foundation of economic resilience, technological leadership and national security. AI, advanced infrastructure and the capacity to build become as important as discovery itself.Yet the report also reveals a striking paradox. The same administration calling for “a new golden age” of US science has simultaneously proposed deep cuts to the federal research enterprise while expanding political influence over the allocation of public research funding. Europe should therefore distinguish between the report's diagnosis and its prescription. The diagnosis, that science has become a strategic asset, is compelling. But the prescription is self-defeating. Long-term technological leadership depends on strong universities, academic freedom and the institutional autonomy that makes scientific discovery possible. This distinction matters. Bush's achievement was never simply to make science serve national strength. It was to establish a division of labour in which governments invested in research without attempting to direct discovery itself. Scientific breakthroughs emerge precisely because researchers retain the freedom to pursue questions whose value cannot yet be demonstrated and whose conclusions cannot be anticipated.Neither China, nor the USAs science becomes more strategically important, the temptation to politicise it inevitably grows. But scientific freedom is not an obstacle to technological leadership, it is an essential precondition.China represents the opposite model. For decades it has integrated science, manufacturing, infrastructure and industrial policy into a single national strategy. Its ability to mobilise resources around critical technologies is formidable. But it does so within an authoritarian system where scientific priorities are increasingly inseparable from political power.Europe should imitate neither model. It should learn from the strategic ambition of the US without importing its growing politicisation of science. And it should learn from China's capacity to build without adopting its concentration of power.Instead, Europe needs a scientific contract of its own. Bush's scientific contract protected the freedom to discover because the defining challenge of the 20th century was producing new knowledge. Europe's next scientific contract must preserve that freedom while ensuring that scientific discoveries can be converted into technological, industrial and strategic capability. Because in a transactional world, Europe's freedom to shape its own future depends on its capacity to build it.Related articlesThe US ‘golden age’ science strategy: what Europeans need to knowEuropean researchers sound the alarm that Trump rule changes will hit cooperationNIH turmoil risks reciprocal EU-US access to health research fundingThis does not mean subordinating free science to competitiveness or industrial policy. On the contrary. Scientific autonomy remains the first principle of Europe's next scientific contract. Governments should not direct scientific discovery. Their responsibility is to ensure that Europe's scientific, industrial, financial and regulatory institutions work together rather than in isolation.Meeting that responsibility requires far more than research funding. European researchers need access to world-class computing infrastructure, advanced laboratories, shared datasets and scientific facilities. Innovative companies need patient capital, testing environments and a genuine single market in which they can scale without facing 27 different regulatory regimes. Public procurement must evolve from purchasing existing technologies to creating markets for new ones. Regulators must become partners in experimentation rather than guardians of yesterday's rules.A connecting architectureEurope does not need to invent the Defense Advanced Research Projects Agency (Darpa) model from scratch. Britain's Aria, Germany's Sprind and Wellcome Leap already show that Europe can build institutions capable of taking high-risk, mission-oriented bets while preserving democratic accountability. The challenge now is not to create more isolated initiatives, but to connect them to Europe's broader scientific, industrial and financial system so that breakthrough discoveries can scale.Above all, Europe must stop treating research, innovation, industrial policy, finance and security as separate policy domains. The challenge is no longer to create excellent institutions in each of these fields, but to make them work as one European innovation system. Europe's strength will increasingly depend not on excellence within institutions, but on excellence across them.Europe's ambition should be neither to imitate the US nor to emulate China. It should demonstrate that scientific freedom, democratic legitimacy and technological capability are not competing objectives, but mutually reinforcing strengths. In an age of geopolitical rivalry, Europe's greatest advantage may ultimately be its ability to attract the world's best talent by combining scientific freedom, democratic openness and technological ambition.Bush's scientific contract helped define the 20th century because it protected the freedom to discover. Europe's challenge is not to abandon that achievement but to extend it. The defining task of Europe's next scientific contract is to preserve the freedom to discover while building Europe's capacity to translate scientific discovery into technological power.Kaare Nielsen is founder of Pomus, a Danish think tank on science and innovation.
Science|Business summer reads of 2026
As most people in the European research and innovation policy bubble are going on a well-deserved summer break, we have come up with a list of our favourite books, podcasts and essays from the past year that ask deeper questions about science, technology and politics.BooksPasteur’s Quadrant: Basic Science and Technological Innovation, by Donald StokesIf you haven’t read Pasteur’s Quadrant yet, now is the time. In the EU and elsewhere, we’re living through a period of dwindling faith that curiosity-driven research automatically leads to economic growth and technological progress. Pasteur’s Quadrant, published in 1997 by the Princeton academic Donald Stokes, is the most influential critique of the standard “linear model” of R&D: the idea that new discoveries made in ivory-tower labs get neatly passed on for commercialisation by start-ups. In reality, Stokes argues, practical applications often inspire more theorical lines of inquiry. Of course, we have long known that things are more complex than the linear model, but even today, it’s still often assumed in Brussels discourse. The book is a useful corrective, and is being used now to argue for new types of scientific institutions. David MatthewsThe Weaponization of Expertise: How Elites Fuel Populism, by Jacob Hale Russel and Dennis PattersonAre society’s problems solvable by technical expertise alone? “If only the benighted would listen,” say Jacob Hale Russel and Dennis Patterson, two professors at Rutgers Law School who got frustrated with how scientists and politicians handled public health communication during the Covid-19 pandemic. In the book, they argue that clichéd mantras about scientific evidence and expertise perpetrated by academics, journalists and politicians have harmed public trust in the very institutions they were trying to defend. Paradoxically, slogans such as “we believe in science,” “follow the science” and “defer to the experts” can fuel mistrust in science, experts and democratic institutions. The authors criticise “condescension” and “technocratic paternalism” in the public discourse and make the case for a more nuanced approach to scientific and expert policy advice that rests on humility, doubt, scepticism and open dialogue. “Most complex social questions in fact revolve around values, not the recitation of unambiguous facts,” they say. Florin ZubascuBreakneck: China's Quest to Engineer the Future, by Dan WangIn this book, Dan Wang compares the structural differences between the US and Chinese industrial policies, but raises a very timely question for innovation policy wonks: how can advanced manufacturing know-how contribute to technology-intensive economic growth? Wang says technology has three components: the tools, the blueprints and patents, and the process knowledge. The third component represents the “proficiency gained from practical experience, which isn’t easily communicated and requires years of implementation.” According to Wang, rather than seeing tools and blueprints as the ultimate ends of technological progress, policymakers should see them as milestones in the training of better scientists and manufacturers. Over the past decades, China has amassed “process knowledge” because capital flowed to complex fabrication facilities, while investors in the West have parked their money in capital-light businesses such as digital platforms or chip companies that focus on design. As it turns out, thanks to its oversized focus on manufacturing, China has gained remarkable advantages in the global technology race. Florin ZubascuBaltic: The Future of Europe, by Oliver MoodyWhat can Europe learn from the nine countries surrounding the Baltic Sea? Alongside the familiar stories about Estonia's digital transformation, the book examines how the region has used technology, resilience, education, governance and long-term thinking to respond to geopolitical, economic and security challenges. Innovation policy wonks might find fresh perspectives on how innovation can strengthen defence, societal resilience and Europe's capacity to adapt in an uncertain world. Whether or not you agree with all of Oliver Moody's conclusions, the book is a useful guide to a region that is increasingly shaping European debates on security, competitiveness and technology. Goda NaujokaityteThe Invention of Nature, by Andrea Wulf This book chronicles the wild and adventurous life of natural science pioneer Alexander von Humboldt who at some point in the 19th century seems to have been just about the most famous person in the world. Through scientific expeditions to the Andes Mountains and to the depths of Siberia, von Humboldt contributed a host of discoveries and concepts. During his life he met and formed relationships with historical figures as different as Johann Wolfgang von Goethe, Simon Bolivar, Thomas Jefferson, Napoleon Bonaparte and Charles Darwin. He is also claimed to be the person in the world with most things named after him, a list that includes an ocean current, a penguin and a region of the Moon. Still venerated in Germany, with numerous scientific institutions named after him, von Humboldt has slipped out of public consciousness in most of the rest of the world. For anyone not familiar with him, this book does a good job of describing his fascinating life. Ole EllekrogCareless People, by Sarah Wynn-WilliamsYou may have heard this referred to as the book Meta doesn’t want you to read. The 2025 memoir from Sarah Wynn-Williams, former director of global public policy at Meta, then just called Facebook, includes explosive claims about everything from a toxic workplace culture to how the company worked with advertisers to target vulnerable teens, and the lengths it was prepared to go to in order to break into China. It’s a fascinating insight into how and why the tech company gradually shifted its approach to policy, whether in the US, Europe or Asia. Meta has denied the allegations in the book, and last year won an emergency ruling to prevent Wynn-Williams from promoting it. In response, the author is now suing her former employer. If that doesn’t make you want to read it. Martin GreenacrePodcastsThe Europeans: Europe’s anti-ElonThis podcast is a great choice for a light-hearted dose of European policy and culture news. Most of it has little to do with research, innovation and technology, but this particular podcast features an interview with Mastadon’s founder Eugen Rochko. He talks about his experience running an open-source, federated, European-made social media platform, and leaving it all behind. The conversation, which starts 14 minutes in, gently encourages us to reflect on what kind of technology we, as Europeans, want to make. Goda NaujokaityteSolarpunk and how we escape dystopiaNew technologies are very often taken from science fiction. Alberto Santos-Dumont, inventor the airship, was inspired as a child by the adventure stories of Jules Verne. OpenAI’s attempt to build a personal assistant with the voice of Scarlett Johansson was lifted from the 2013 film Her, completely ignoring the movie’s cautionary message. So if we want better tech, we need to imagine it first. Unfortunately, the state of current sci-fi is relentlessly dystopian, giving inventors precious few ideas or hope. However, a new genre, Solarpunk, which envisages a technologically advanced but ecologically harmonious future, is now taking off. The actual tech the genre imagines, such as permaculture, renewable energy or community repair workshops, while nice, isn’t all that inspiring or ambitious. But it’s a first step towards rescuing sci-fi from its pessimistic Blade Runner rut. David MatthewsEveryday AbundanceLaunched in June, Everyday Abundance is a podcast that tells the stories of the inventions we now take so for granted that we barely given them a second thought. For example, the washing machine, which liberated women from a lifetime “bent over washtubs and washboards.” Or modern dentistry, which ended the reality that “tooth pain was simply part of human life.” Historians of technology, Virginia Postrel and Charles C Mann are very much on the optimistic end of the spectrum when it comes to the capacity of invention to improve human life. Here, they set out their case: if it wasn’t for progress, you might be hunched over a washtub with toothache rather than reading these words. David Matthews‘We will not know what we lost’: Conservation fallout a year after USAID shutdownSince his return to the White House, Donald Trump has been on a mission to undermine science. He slashed jobs at federal agencies, terminated grants in some research areas, took unprecedented control over university affairs and, within hours of his inauguration, suspended the US Agency for International Development. While its initial focus was to administer health and food aid around the world, it had since expanded to conservation projects. The result? Some of these projects were stopped abruptly. In this Mongabay podcast, environmental reporter Michelle Nijhuis tells the story of the EcoGuard conservation programme in Liberia, whose local patrols had helped protect rainforests, monitor endangered wildlife and track illegal threats. From one day to the next, these were left without salaries. Luckily, she notes, the initiative was able to get emergency funding from international NGOs, but its future remains “incredibly uncertain.” Juliette PortalaEssaysThe Mars Delusion, by Henry WismayerWhy is humankind so fixated on establishing a colony on Mars? asks London-based writer Henry Wismayer. From space evangelists promoting Martian settlement as an insurance policy, to billionaire Jeff Bezos, who said humans should settle on Mars “because it’s cool,” the mission is not running short of advocates. However, in this essay, Wismayer reminds us that some critics expect any future Mars pioneer to end up “irradiated, sick, mad and dead.” Scientists have already looked into the possible effects of prolonged exposure to Martian gravity, and it’s not pretty: muscle shrinking, bones weakening, changes to the central nervous system and other biological modifications to make us all reconsider the journey. “Some researchers have forecast that the future settler, after generations of evolutionary conditioning, will look less like an Übermensch and more like ET,” Wismayer writes. Juliette Portala
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